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» Adaptive Background Mixture Models for Real-Time Tracking
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IROS
2007
IEEE
189views Robotics» more  IROS 2007»
14 years 1 months ago
Person following with a mobile robot using binocular feature-based tracking
Abstract— We present the Binocular Sparse Feature Segmentation (BSFS) algorithm for vision-based person following with a mobile robot. BSFS uses Lucas-Kanade feature detection an...
Zhichao Chen, Stanley T. Birchfield
CVPR
2005
IEEE
14 years 1 months ago
Online Selecting Discriminative Tracking Features Using Particle Filter
The paper proposes a method to keep the tracker robust to background clutters by online selecting discriminative features from a large feature space. Furthermore, the feature sele...
Jianyu Wang, Xilin Chen, Wen Gao
CVPR
2005
IEEE
14 years 9 months ago
Combining Object and Feature Dynamics in Probabilistic Tracking
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
FGR
2000
IEEE
163views Biometrics» more  FGR 2000»
14 years 1 days ago
Tracking Interacting People
A computer vision system for tracking multiple people in relatively unconstrained environments is described. Trackerformed at three levels of abstraction: regions, people and grou...
Stephen J. McKenna, Sumer Jabri, Zoran Duric, Harr...
BMVC
2010
13 years 5 months ago
On-line Adaption of Class-specific Codebooks for Instance Tracking
Off-line trained class-specific object detectors are designed to detect any instance of the class in a given image or video sequence. In the context of object tracking, however, o...
Juergen Gall, Nima Razavi, Luc J. Van Gool